Abstract
Large open spaces, e.g., beaches, cattle-grazing grounds, etc., often need to be monitored for security or other reasons. In many cases, monitoring from the air provides the widest and most effective coverage. However, due to the cost of air-based monitoring, such aerial monitoring is often not possible, putting individuals or assets at risk or causing loss of revenue. This disclosure describes techniques to deploy small aircraft, e.g., kites, blimps, low-powered drones, etc. to monitor a given area. A video feed from the aircraft is analyzed using a trained machine-learning model to automatically detect situations that meet safety or compliance criteria, e.g., a swimmer at a beach getting far from the coast, cattle straying into forbidden territory, etc., and to automatically provide alerts.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Mayster, Yan and Shucker, Brian, "Airship-based security and monitoring with machine learning", Technical Disclosure Commons, (January 09, 2020)
https://www.tdcommons.org/dpubs_series/2859